Non‐native prey availability and over‐compensatory density dependence drive population dynamics of a native fish predator
Bibliographic record
Abstract
Understanding the factors that regulate population dynamics is crucial for conserving imperiled species. Bull trout (Salvelinus confluentus), a piscivorous salmonid and one of North America's most threatened cold-water species, has declined significantly due to habitat loss, overfishing, invasive species, and climate change. While recovery efforts have primarily targeted these threats, the role of prey availability in influencing bull trout population dynamics under multiple stressors remains poorly understood. Using a stage-based integrated population model, we quantified the effects of non-native prey availability (kokanee; Oncorhynchus nerka), angling pressure, climatic variation, and density-dependent processes on bull trout population dynamics in Lake Koocanusa, a transboundary reservoir and river system (United States and Canada), over a 40-year period (1980-2023). Our results show that bull trout populations are regulated by density-dependent processes, including over-compensation in sub-adult recruitment and reduced adult survival at high densities. Increased kokanee biomass and restricted harvest significantly enhanced bull trout survival and abundance, whereas reduced water availability had a limited negative effect on sub-adult production. Model simulations indicate that as kokanee biomass availability increases, the number of bull trout that can be sustainably harvested also increases. In fact, a modest annual fishery (300 individuals) can be sustained, especially under moderate to high kokanee biomass conditions. These results underscore the importance of prey availability, including non-native species, in supporting bull trout populations. Effective management of threatened apex fish predators like bull trout requires addressing the complex interplay between environmental threats, prey dynamics, and density-dependent mechanisms across all life stages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".